This research addresses pressing environmental concerns by proposing a novel optimization framework for combined economic and emissions dispatch (CEED) in microgrids, aiming to enhance their viability as a sustainable alternative to traditional power systems. The framework employs the predatory pelican optimization algorithm (PPOA), a hybrid optimization methodology merging the marine predators algorithm and pelican optimization algorithm, to resolve the environmental and economic scheduling challenges of microgrids, ensuring sustainable and efficient operation. This approach simultaneously optimizes emissions, economics, and grid stability, addressing the multi-dimensional nature of CEED problems. The PPOA's adaptability to inherent uncertainties in data is a key strength. Effective constraint management ensures operational consistency and sustainability, while the utilization of MATLAB underscores the practical applicability and computational robustness of the proposed methodologies in power systems optimization. As results demonstrate that PPOA achieved a 10-15% reduction in total generation costs, a 20% decrease in emissions, and a 12% reduction in power losses compared to traditional algorithm like HHO, highlighting its superior performance and practical feasibility. The ultimate goal is to significantly improve microgrid environmental friendliness and overall viability, thereby contributing to a paradigm shift towards sustainable energy systems in the face of escalating environmental challenges.